Control (management)

Voltage

Engineering

MATLAB

Biology

Control engineering

Operating system

Computer science

Grid

Maximum power point tracking

Controller (irrigation)

Mathematics

Inverter

Agronomy

Maximum power principle

Artificial intelligence

Geometry

Control theory (sociology)

Photovoltaic system

Electrical engineering

Energy Procedia

Over the past decades, meta-heuristic optimization techniques have become surprisingly very popular due to their flexibility and local optima avoidance capability. This paper uses the Whale Optimization Algorithm (WOA), a swarm-based technique to tune the Proportional-Integral (PI) based Maximum Power Point Tracking (MPPT) controllers of a grid-connected solar Photovoltaic (PV) system. The results of the PI-based Incremental Conductance (IC) MPPT technique are compared with both the conventional incremental conductance and the Perturb & Observe (P&O) MPPT techniques. Various modes of the PI controller are used. I, PI and Fractional order PI (FOPI) gain parameters are determined using WOA. Performance indices are applied to estimate the best parameters of the PI controller. This paper aims to show the effect of using PI-based MPPT controllers on enhancing the performance of a 400-kW grid-connected PV system. Simulation results show the capability of PI-based MPPT controllers on improving the performance of the PV system. It demonstrates the superiority of FOPI controllers over the other modes in enhancing system performance. The proposed work is simulated using MATLAB SIMULINK.

Whale inspired algorithm based MPPT controllers for grid-connected solar photovoltaic system